The paper presents some selected results of research on applications of artificial intelligence to the optimization of main ship design parameters and hull shape coefficients with the ship transport efficiency as an objective function. Basics of ship transport formulation are concisely discussed, together with examples for different approaches to optimization. An example of neural network use for the determination of ship transport efficiency is given with an assessment of its ability for data generalization. Moreover, two optimization procedures are presented: one using genetic algorithms and the other with simulated annealing approach. Both procedures lead to the improvement of ship transport efficiency